Current Mathematical Models for Analyzing Anti-Malarial Antibody Data with an Eye to Malaria Elimination and Eradication.
Current Mathematical Models for Analyzing Anti-Malarial Antibody Data with an Eye to Malaria Elimination and Eradication.
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DOI：
10.1155/2015/738030
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发表时间：
2015
影响因子：
4.1
通讯作者：
Drakeley CJ
中科院分区：
文献类型：
--
作者：
Sepúlveda N;Stresman G;White MT;Drakeley CJ
过去十年，全世界的疟疾负担稳步减少。随着各国在不久的将来以消除疾病为目标，由于取样时受感染的个体或蚊子数量减少，流行的寄生虫感染或昆虫接种率越来越不能说明潜在的疟疾负担。为了克服这一问题，基于针对特定疟疾抗原的抗体的替代措施最近引起了人们对疟疾流行病学的兴趣，因为有可能在没有感染者的情况下估计过去的疾病暴露情况。本文旨在回顾目前用于抗体数据分析的数学模型和相应的统计方法。这些模型的应用以赤道几内亚、巴西亚马逊地区和肯尼亚西部高地的三个数据集为例。还就在消除疟疾的背景下使用这些模型的未来挑战进行了简要讨论。
The last decade has witnessed a steady reduction of the malaria burden worldwide. With various countries targeting disease elimination in the near future, the popular parasite infection or entomological inoculation rates are becoming less and less informative of the underlying malaria burden due to a reduced number of infected individuals or mosquitoes at the time of sampling. To overcome such problem, alternative measures based on antibodies against specific malaria antigens have gained recent interest in malaria epidemiology due to the possibility of estimating past disease exposure in absence of infected individuals. This paper aims then to review current mathematical models and corresponding statistical approaches used in antibody data analysis. The application of these models is illustrated with three data sets from Equatorial Guinea, Brazilian Amazonia region, and western Kenyan highlands. A brief discussion is also carried out on the future challenges of using these models in the context of malaria elimination.